fix(weather): Ensure model year is interpreted correctly

dragonfly_grasshopper/json/DF_Create_EPW.json

@@ -1,5 +1,5 @@
 {
-  "version": "1.5.0", 
+  "version": "1.5.1", 
   "nickname": "CreateEPW", 
   "outputs": [
     [
@@ -122,7 +122,7 @@
       "access": "item", 
       "name": "base_epw_", 
       "description": "File path to an optional .epw to fill empty slots for data\nthat has not been connected here.", 
-      "type": "System.Object", 
+      "type": "string", 
       "default": null
     }, 
     {
@@ -134,7 +134,7 @@
     }
   ], 
   "subcategory": "4 :: AlternativeWeather", 
-  "code": "\nimport math\n\ntry:\n    from ladybug.epw import EPW\n    from ladybug.wea import Wea\n    from ladybug.datacollection import HourlyContinuousCollection\n    from ladybug.sunpath import Sunpath\n    from ladybug.datatype.temperature import Temperature\n    from ladybug.datatype.fraction import Fraction, RelativeHumidity\n    from ladybug.datatype.speed import Speed\n    from ladybug.datatype.angle import Angle\n    from ladybug.datatype.energyflux import EnergyFlux\n    from ladybug.datatype.illuminance import Illuminance\n    from ladybug.datatype.pressure import Pressure\n    from ladybug.datatype.distance import Distance\n    from ladybug.psychrometrics import rel_humid_from_db_dpt\nexcept ImportError as e:\n    raise ImportError('\\nFailed to import ladybug:\\n\\t{}'.format(e))\n\ntry:\n    from ladybug_{{cad}}.{{plugin}} import all_required_inputs\nexcept ImportError as e:\n    raise ImportError('\\nFailed to import ladybug_{{cad}}:\\n\\t{}'.format(e))\n\n\ndef check_data(name, data_coll, data_type, unit, is_leap_year):\n    assert isinstance(data_coll, HourlyContinuousCollection), \\\n        '{} must be an hourly continuous data collection. Got {}.'.format(\n            name, type(data_coll))\n    assert data_coll.header.analysis_period.is_annual, '{} analysis_period must ' \\\n        'be annual. Got {}'.format(header.analysis_period)\n    assert data_coll.header.analysis_period.is_leap_year == is_leap_year, \\\n        '{} analysis_period must is_leap_year must match across input data collections.'\n    assert isinstance(data_coll.header.data_type, data_type), '{} data_type is not {}. '\\\n        'Got {}.'.format(name, data_type(), data_coll.header.data_type)\n    assert data_coll.header.unit == unit, '{} unit is not {}. '\\\n        'Got {}.'.format(name, unit, data_coll.header.unit)\n    return data_coll.values\n\n\nif all_required_inputs(ghenv.Component) and _run:\n    # initialize the EPW\n    if base_epw_ is not None:\n        epw_obj = EPW(base_epw_)\n        leap_yr = epw_obj.is_leap_year\n    else:\n        if _model_year_:\n            leap_yr = _model_year_.header.analysis_period.is_leap_year\n        else:\n            leap_yr = False\n        epw_obj = EPW.from_missing_values(is_leap_year=leap_yr)\n    \n    # assign data to the EPW\n    epw_obj.location = _location\n    if _dry_bulb_temp_:\n        epw_obj.dry_bulb_temperature.values = check_data(\n            '_dry_bulb_temp_', _dry_bulb_temp_, Temperature, 'C', leap_yr)\n    if _dew_point_temp_:\n        epw_obj.dew_point_temperature.values = check_data(\n            '_dew_point_temp_', _dew_point_temp_, Temperature, 'C', leap_yr)\n    if _wind_speed_:\n        epw_obj.wind_speed.values = check_data(\n            '_wind_speed_', _wind_speed_, Speed, 'm/s', leap_yr)\n    if _wind_direction_:\n        epw_obj.wind_direction.values = check_data(\n            '_wind_direction_', _wind_direction_, Angle, 'degrees', leap_yr)\n    if _direct_normal_rad_:\n        epw_obj.direct_normal_radiation.values = _direct_normal_rad_.values\n    if _diffuse_horiz_rad_:\n        epw_obj.diffuse_horizontal_radiation.values = _diffuse_horiz_rad_.values\n    if _horiz_infrared_rad_:\n        epw_obj.horizontal_infrared_radiation_intensity.values = check_data(\n            '_horiz_infrared_rad_', _horiz_infrared_rad_, EnergyFlux, 'W/m2', leap_yr)\n    if _direct_normal_ill_:\n        epw_obj.direct_normal_illuminance.values = check_data(\n            '_direct_normal_ill_', _direct_normal_ill_, Illuminance, 'lux', leap_yr)\n    if _diffuse_horiz_ill_:\n        epw_obj.diffuse_horizontal_illuminance.values = check_data(\n            '_diffuse_horiz_ill_', _diffuse_horiz_ill_, Illuminance, 'lux', leap_yr)\n    if _total_sky_cover_:\n        epw_obj.total_sky_cover.values = check_data(\n            '_total_sky_cover_', _total_sky_cover_, Fraction, 'tenths', leap_yr)\n        epw_obj.opaque_sky_cover.values = _total_sky_cover_.values\n    if _atmos_pressure_:\n        epw_obj.atmospheric_station_pressure.values = check_data(\n            '_atmos_pressure_', _atmos_pressure_, Pressure, 'Pa', leap_yr)\n    if _visibility_:\n        epw_obj.visibility.values = check_data(\n            '_visibility_', _visibility_, Distance, 'km', leap_yr)\n    if _ceiling_height_:\n        epw_obj.ceiling_height.values = check_data(\n            '_ceiling_height_', _ceiling_height_, Distance, 'm', leap_yr)\n    if _model_year_:\n        epw_obj.years.values = _model_year_.values\n    \n    # calculate properties that are derived from other inputs\n    if _dry_bulb_temp_ and _dew_point_temp_:\n        rel_humid = HourlyContinuousCollection.compute_function_aligned(\n            rel_humid_from_db_dpt, [_dry_bulb_temp_, _dew_point_temp_],\n            RelativeHumidity(), '%')\n        epw_obj.relative_humidity.values = rel_humid.values\n    if _direct_normal_rad_ and _diffuse_horiz_rad_:\n        wea = Wea(_location, _direct_normal_rad_, _diffuse_horiz_rad_)\n        epw_obj.global_horizontal_radiation.values = wea.global_horizontal_irradiance.values\n    if _direct_normal_ill_ and _diffuse_horiz_ill_:\n        glob_horiz = []\n        sp = Sunpath.from_location(_location)\n        sp.is_leap_year = leap_yr\n        for dt, dni, dhi in zip(_direct_normal_ill_.datetimes,\n                _direct_normal_ill_, _diffuse_horiz_ill_):\n            sun = sp.calculate_sun_from_date_time(dt)\n            glob_horiz.append(dhi + dni * math.sin(math.radians(sun.altitude)))\n        epw_obj.global_horizontal_illuminance.values = glob_horiz\n", 
+  "code": "\nimport math\n\ntry:\n    from ladybug.epw import EPW\n    from ladybug.wea import Wea\n    from ladybug.datacollection import HourlyContinuousCollection\n    from ladybug.sunpath import Sunpath\n    from ladybug.datatype.temperature import Temperature\n    from ladybug.datatype.fraction import Fraction, RelativeHumidity\n    from ladybug.datatype.speed import Speed\n    from ladybug.datatype.angle import Angle\n    from ladybug.datatype.energyflux import EnergyFlux\n    from ladybug.datatype.illuminance import Illuminance\n    from ladybug.datatype.pressure import Pressure\n    from ladybug.datatype.distance import Distance\n    from ladybug.psychrometrics import rel_humid_from_db_dpt\nexcept ImportError as e:\n    raise ImportError('\\nFailed to import ladybug:\\n\\t{}'.format(e))\n\ntry:\n    from ladybug_{{cad}}.{{plugin}} import all_required_inputs\nexcept ImportError as e:\n    raise ImportError('\\nFailed to import ladybug_{{cad}}:\\n\\t{}'.format(e))\n\n\ndef check_data(name, data_coll, data_type, unit, is_leap_year):\n    assert isinstance(data_coll, HourlyContinuousCollection), \\\n        '{} must be an hourly continuous data collection. Got {}.'.format(\n            name, type(data_coll))\n    assert data_coll.header.analysis_period.is_annual, '{} analysis_period must ' \\\n        'be annual. Got {}'.format(header.analysis_period)\n    assert data_coll.header.analysis_period.is_leap_year == is_leap_year, \\\n        '{} analysis_period must is_leap_year must match across input data collections.'\n    assert isinstance(data_coll.header.data_type, data_type), '{} data_type is not {}. '\\\n        'Got {}.'.format(name, data_type(), data_coll.header.data_type)\n    assert data_coll.header.unit == unit, '{} unit is not {}. '\\\n        'Got {}.'.format(name, unit, data_coll.header.unit)\n    return data_coll.values\n\n\nif all_required_inputs(ghenv.Component) and _run:\n    # initialize the EPW\n    if base_epw_ is not None:\n        epw_obj = EPW(base_epw_)\n        leap_yr = epw_obj.is_leap_year\n    else:\n        if _model_year_:\n            leap_yr = _model_year_.header.analysis_period.is_leap_year\n        else:\n            leap_yr = False\n        epw_obj = EPW.from_missing_values(is_leap_year=leap_yr)\n\n    # assign data to the EPW\n    epw_obj.location = _location\n    if _dry_bulb_temp_:\n        epw_obj.dry_bulb_temperature.values = check_data(\n            '_dry_bulb_temp_', _dry_bulb_temp_, Temperature, 'C', leap_yr)\n    if _dew_point_temp_:\n        epw_obj.dew_point_temperature.values = check_data(\n            '_dew_point_temp_', _dew_point_temp_, Temperature, 'C', leap_yr)\n    if _wind_speed_:\n        epw_obj.wind_speed.values = check_data(\n            '_wind_speed_', _wind_speed_, Speed, 'm/s', leap_yr)\n    if _wind_direction_:\n        epw_obj.wind_direction.values = check_data(\n            '_wind_direction_', _wind_direction_, Angle, 'degrees', leap_yr)\n    if _direct_normal_rad_:\n        epw_obj.direct_normal_radiation.values = _direct_normal_rad_.values\n    if _diffuse_horiz_rad_:\n        epw_obj.diffuse_horizontal_radiation.values = _diffuse_horiz_rad_.values\n    if _horiz_infrared_rad_:\n        epw_obj.horizontal_infrared_radiation_intensity.values = check_data(\n            '_horiz_infrared_rad_', _horiz_infrared_rad_, EnergyFlux, 'W/m2', leap_yr)\n    if _direct_normal_ill_:\n        epw_obj.direct_normal_illuminance.values = check_data(\n            '_direct_normal_ill_', _direct_normal_ill_, Illuminance, 'lux', leap_yr)\n    if _diffuse_horiz_ill_:\n        epw_obj.diffuse_horizontal_illuminance.values = check_data(\n            '_diffuse_horiz_ill_', _diffuse_horiz_ill_, Illuminance, 'lux', leap_yr)\n    if _total_sky_cover_:\n        epw_obj.total_sky_cover.values = check_data(\n            '_total_sky_cover_', _total_sky_cover_, Fraction, 'tenths', leap_yr)\n        epw_obj.opaque_sky_cover.values = _total_sky_cover_.values\n    if _atmos_pressure_:\n        epw_obj.atmospheric_station_pressure.values = check_data(\n            '_atmos_pressure_', _atmos_pressure_, Pressure, 'Pa', leap_yr)\n    if _visibility_:\n        epw_obj.visibility.values = check_data(\n            '_visibility_', _visibility_, Distance, 'km', leap_yr)\n    if _ceiling_height_:\n        epw_obj.ceiling_height.values = check_data(\n            '_ceiling_height_', _ceiling_height_, Distance, 'm', leap_yr)\n    if _model_year_:\n        epw_obj.years.values = [int(val) for val in _model_year_.values]\n\n    # calculate properties that are derived from other inputs\n    if _dry_bulb_temp_ and _dew_point_temp_:\n        rel_humid = HourlyContinuousCollection.compute_function_aligned(\n            rel_humid_from_db_dpt, [_dry_bulb_temp_, _dew_point_temp_],\n            RelativeHumidity(), '%')\n        epw_obj.relative_humidity.values = rel_humid.values\n    if _direct_normal_rad_ and _diffuse_horiz_rad_:\n        wea = Wea(_location, _direct_normal_rad_, _diffuse_horiz_rad_)\n        epw_obj.global_horizontal_radiation.values = wea.global_horizontal_irradiance.values\n    if _direct_normal_ill_ and _diffuse_horiz_ill_:\n        glob_horiz = []\n        sp = Sunpath.from_location(_location)\n        sp.is_leap_year = leap_yr\n        for dt, dni, dhi in zip(_direct_normal_ill_.datetimes,\n                _direct_normal_ill_, _diffuse_horiz_ill_):\n            sun = sp.calculate_sun_from_date_time(dt)\n            glob_horiz.append(dhi + dni * math.sin(math.radians(sun.altitude)))\n        epw_obj.global_horizontal_illuminance.values = glob_horiz\n", 
   "category": "Dragonfly", 
   "name": "DF Create EPW", 
   "description": "Create a custom EPW object from a location and data collections of annual\nhourly data.\n-"

dragonfly_grasshopper/src/DF Create EPW.py

@@ -49,7 +49,7 @@
 
 ghenv.Component.Name = 'DF Create EPW'
 ghenv.Component.NickName = 'CreateEPW'
-ghenv.Component.Message = '1.5.0'
+ghenv.Component.Message = '1.5.1'
 ghenv.Component.Category = "Dragonfly"
 ghenv.Component.SubCategory = '4 :: AlternativeWeather'
 ghenv.Component.AdditionalHelpFromDocStrings = '3'
@@ -105,7 +105,7 @@ def check_data(name, data_coll, data_type, unit, is_leap_year):
         else:
             leap_yr = False
         epw_obj = EPW.from_missing_values(is_leap_year=leap_yr)
-    
+
     # assign data to the EPW
     epw_obj.location = _location
     if _dry_bulb_temp_:
@@ -147,8 +147,8 @@ def check_data(name, data_coll, data_type, unit, is_leap_year):
         epw_obj.ceiling_height.values = check_data(
             '_ceiling_height_', _ceiling_height_, Distance, 'm', leap_yr)
     if _model_year_:
-        epw_obj.years.values = _model_year_.values
-    
+        epw_obj.years.values = [int(val) for val in _model_year_.values]
+
     # calculate properties that are derived from other inputs
     if _dry_bulb_temp_ and _dew_point_temp_:
         rel_humid = HourlyContinuousCollection.compute_function_aligned(